We propose a probabilistic, generative account of configural learning phenomena in classical conditioning. Configural learning experiments probe how animals discriminate and gener...
Aaron C. Courville, Nathaniel D. Daw, David S. Tou...
As sensing technologies become increasingly distributed and democratized, citizens and novice users are becoming responsible for the kinds of data collection and analysis that have...
Wesley Willett, Paul M. Aoki, Neil Kumar, Sushmita...
Mixture models, such as Gaussian Mixture Model, have been widely used in many applications for modeling data. Gaussian mixture model (GMM) assumes that data points are generated fr...
Traditional data-oriented programming languages such as dataflow s and stream languages provide a natural abstraction for parallel programming. In these languages, a developer fo...
—Direct volume rendering is an important tool for visualizing complex data sets. However, in the process of generating 2D images from 3D data, information is lost in the form of ...